Tableau Developer

We are currently seeking a Data Analyst to join our team in Bengaluru, Karnataka, India.

Role Summary

The Data Analyst is responsible for transforming data into actionable insights that support business decisions.

This role works closely with Salesforce data and the Tableau analytics stack, including Tableau Prep, Tableau, Tableau Next, and Tableau Pulse, to prepare data, build dashboards, monitor key metrics, and deliver clear reporting to stakeholders. Python is used to support data preparation, automation, and deeper analysis where needed.

Key Responsibilities

• Collect, clean, transform, and validate data from multiple business systems, with a strong focus on Salesforce data sources
• Build and maintain data preparation workflows using Tableau Prep
• Create, enhance, and support interactive dashboards and reports in Tableau
• Develop analytics experiences in Tableau Next to support scalable, self-service insight delivery
• Use Tableau Pulse to monitor key business metrics and surface timely, actionable alerts and insights
• Use Python to automate repetitive analysis tasks, support data transformation, and perform advanced data analysis
• Partner with business users to define reporting requirements, KPIs, and success metrics
• Translate business questions into structured analytical approaches and clear visual outputs
• Identify data quality issues, reconcile discrepancies, and support data governance practices
• Document data definitions, calculation logic, dashboard assumptions, and report usage guidance
• Monitor dashboard performance and improve usability, clarity, and adoption
• Support ad hoc analysis and recurring reporting needs
• Help standardize metrics and reporting conventions across the organization

Key Skills

• Tableau dashboard development and visualization
• Tableau Prep data preparation and transformation
• Tableau Next and Tableau Pulse
• Salesforce data analysis and reporting
• Python for data analysis and automation
• SQL for querying and analysis
• KPI design and business metrics definition
• Data quality validation and reconciliation
• Strong analytical thinking and problem-solving

Clear communication and stakeholder collaboration